Relevant bibliographies by topics / Complexity

Academic literature on the topic 'Complexity'

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Published: 4 June 2021
Last updated: 7 July 2024

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Journal articles on the topic "Complexity"

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Chow, Robert. "Complexity of Complexin." Biophysical Journal 106, no. 2 (January 2014): 11a. http://dx.doi.org/10.1016/j.bpj.2013.11.110.

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BLOWS, M. W. "Complexity for complexity's sake?" Journal of Evolutionary Biology 20, no. 1 (January 2007): 39–44. http://dx.doi.org/10.1111/j.1420-9101.2006.01241.x.

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Shoemaker, Jessica. "Complexity's Shadow: American Indian Property, Sovereignty, and the Future." Michigan Law Review, no. 115.4 (2017): 487. http://dx.doi.org/10.36644/mlr.115.4.complexity.

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This Article offers a new perspective on the challenges of the modern American Indian land tenure system. While some property theorists have renewed focus on isolated aspects of Indian land tenure, including the historic inequities of colonial takings of Indian lands, this Article argues that the complexity of today’s federally imposed reservation property system does much of the same colonizing work that historic Indian land policies—from allotment to removal to termination—did overtly. But now, these inequities are largely overshadowed by the daunting complexity of the whole land tenure structure. This Article introduces a new taxonomy of complexity in American Indian land tenure and explores in particular how the recent trend of hypercategorizing property and sovereignty interests into ever-more granular and interacting jurisdictional variables has exacerbated development and self-governance challenges in Indian country. This structural complexity serves no adequate purpose for Indian landowners or Indian nations and, instead, creates perverse incentives to grow the federal oversight role. Complexity begets complexity, and this has created a self-perpetuating and inefficient cycle of federal control. Stepping back and reviewing Indian land tenure in its entirety—as a whole complex, dynamic, and ultimately adaptable system—allows the introduction of new, and potentially fruitful, management techniques borrowed from social and ecological sciences. Top-down Indian land reforms have consistently intensified complexity’s costs. This Article explores how emphasizing grassroots experimentation and local flexibility instead can create critical space for more radical, reservation-by-reservation transformations of local property systems into the future.
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Pöltner, P., and T. Grechenig. "Organic Finance Framework: Aligning Financing Complexity with Organisational Complexity (for Innovative Companies)." International Journal of Trade, Economics and Finance 11, no. 6 (December 2020): 156–62. http://dx.doi.org/10.18178/ijtef.2020.11.6.682.

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The organic finance framework is a new tool for managing the challenges of corporate financing. This framework is especially useful for small and medium-sized enterprises in the time of a crisis, such as the COVID-19 pandemic. At its core, the framework forces a rethink of the manner in which companies initiate their financing approach. In contrast to finding potential external sources of finance, the organic finance framework starts by looking at the relevant stakeholders of the company. Alternative financing methods, such as crowdfunding and crowdinvesting, have demonstrated that companies can work with potential future customers at an early stage in the company lifecycle to finance the development of an offering. Thus, the organic finance framework presents a global structural visualisation of the corporate financing domain that can help business owners to better align the lifecycle of a company with its funding sources.
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Read, Dwight, and Claes Andersson. "Cultural complexity and complexity evolution." Adaptive Behavior 28, no. 5 (January 20, 2019): 329–58. http://dx.doi.org/10.1177/1059712318822298.

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We review issues stemming from current models regarding the drivers of cultural complexity and cultural evolution. We disagree with the implication of the treadmill model, based on dual-inheritance theory, that population size is the driver of cultural complexity. The treadmill model reduces the evolution of artifact complexity, measured by the number of parts, to the statistical fact that individuals with high skills are more likely to be found in a larger population than in a smaller population. However, for the treadmill model to operate as claimed, implausibly high skill levels must be assumed. Contrary to the treadmill model, the risk hypothesis for the complexity of artifacts relates the number of parts to increased functional efficiency of implements. Empirically, all data on hunter-gatherer artifact complexity support the risk hypothesis and reject the treadmill model. Still, there are conditions under which increased technological complexity relates to increased population size, but the dependency does not occur in the manner expressed in the treadmill model. Instead, it relates to population size when the support system for the technology requires a large population size. If anything, anthropology and ecology suggest that cultural complexity generates high population density rather than the other way around.
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Goldreich, Oded, Rafail Ostrovsky, and Erez Petrank. "Computational Complexity and Knowledge Complexity." SIAM Journal on Computing 27, no. 4 (August 1998): 1116–41. http://dx.doi.org/10.1137/s0097539795280524.

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LINIAL, NATI, and ADI SHRAIBMAN. "Learning Complexity vs Communication Complexity." Combinatorics, Probability and Computing 18, no. 1-2 (March 2009): 227–45. http://dx.doi.org/10.1017/s0963548308009656.

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This paper has two main focal points. We first consider an important class of machine learning algorithms: large margin classifiers, such as Support Vector Machines. The notion of margin complexity quantifies the extent to which a given class of functions can be learned by large margin classifiers. We prove that up to a small multiplicative constant, margin complexity is equal to the inverse of discrepancy. This establishes a strong tie between seemingly very different notions from two distinct areas.In the same way that matrix rigidity is related to rank, we introduce the notion of rigidity of margin complexity. We prove that sign matrices with small margin complexity rigidity are very rare. This leads to the question of proving lower bounds on the rigidity of margin complexity. Quite surprisingly, this question turns out to be closely related to basic open problems in communication complexity, e.g., whether PSPACE can be separated from the polynomial hierarchy in communication complexity.Communication is a key ingredient in many types of learning. This explains the relations between the field of learning theory and that of communication complexity [6, l0, 16, 26]. The results of this paper constitute another link in this rich web of relations. These new results have already been applied toward the solution of several open problems in communication complexity [18, 20, 29].
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Lachish, Oded, Ilan Newman, and Asaf Shapira. "Space Complexity Vs. Query Complexity." computational complexity 17, no. 1 (April 2008): 70–93. http://dx.doi.org/10.1007/s00037-008-0239-z.

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Iván Tarride, Mario. "The complexity of measuring complexity." Kybernetes 42, no. 2 (February 2013): 174–84. http://dx.doi.org/10.1108/03684921311310558.

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Barton, C. Michael. "Complexity, Social Complexity, and Modeling." Journal of Archaeological Method and Theory 21, no. 2 (October 26, 2013): 306–24. http://dx.doi.org/10.1007/s10816-013-9187-2.

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Dissertations / Theses on the topic "Complexity"

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Baumler, Raphaël. "La sécurité de marché et son modèle maritime : entre dynamiques du risque et complexité des parades : les difficultés pour construire la sécurité." Thesis, Evry-Val d'Essonne, 2009. http://www.theses.fr/2009EVRY0024/document.

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Modèles de développement, capitalisme et industrialisme sont de grandes dynamiques du risque par leur capacité à transformer le social. Au niveau des firmes, l’innovation continue et la concurrence obligent à l’ajustement permanent. Soumises aux propriétaires, les firmes se focalisent sur le risque financier. Les autres risques lui sont subordonnés. Les dynamiques internes du risque évoluent au rythme d’impératifs externes. La compétition justifie réductions de coûts et réorganisations déstabilisantes. La sécurité a pour objectif la limitation des conditions de réalisation des risques. Construction sociale complexe, la sécurité voit localement la fusion d’hommes, d’outils dans une organisation. Globalement, l’enjeu de la sécurité est la maîtrise du niveau de risque et son coût. Comme pour l’armateur du navire, la direction de l’unité possède les clés de la sécurité. Elle arbitre entre les budgets et joue la concurrence entre les territoires. En assurant l’impunité, l’équivalence et la non-discrimination, le droit international garantit une mise en concurrence de tous les États. Avec la Mondialisation, nous entrons dans l’ère de la sécurité de marché. La sécurité est vue comme un facteur de production. Dans la concurrence, les dirigeants l’intègrent dans leurs stratégies, notamment lors des choix d’implantation géographique et des répartitions budgétaires. En sélectionnant les participants, la direction produit une représentation univoque de la sécurité en phase avec ses paradigmes. La rénovation de la sécurité dans les unités productives se joue localement mais aussi globalement en découvrant les complexités des dynamiques du risque et de la construction de la sécurité
Models of development, capitalism and industrialism are also big dynamics of risk by their ability altering social world. At the level of firms, innovation and competition requires ongoing adjustment. Subject to their owners, companies focus on financial risk. Other risks are subordinate to the primary target. The dynamics of risk are changing the firm at the rate of external demands. The competition justifies harmful cost reductions and destabilizing re-engineering. The aim of safety is to reduce the uprising conditions of risk. Safety is a complex social building. Locally, safety seems a melt of man and tools within an organization. Overall, control of the safety is a challenge between risk and cost in the unit. Between cost and efficiency, management makes its own choice. As the shipowner and his vessel, the factory management has the keys to safety. It arbitrates between budgets and plays competition between territories. Ensuring impunity, equivalence and non-discrimination, international law guarantees competition between all States and flags. With globalization, we entered the era of the safety market. Safety is one of the production factors in global competition. Business leaders incorporate it into their overall strategies. With this factor in mind they choose their factories geographical location but also the allocation of budgets inside the firm. In selecting safety participants, the Executive create a unique picture of what safety is that corresponds to their paradigms. The rebuilding of safety in production units is played locally but also globally and by discovering the complexities of the dynamics of risk and the way of building safety
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Rubiano, Thomas. "Implicit Computational Complexity and Compilers." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCD076/document.

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Complexity theory helps us predict and control resources, usually time and space, consumed by programs. Static analysis on specific syntactic criterion allows us to categorize some programs. A common approach is to observe the program’s data’s behavior. For instance, the detection of non-size-increasing programs is based on a simple principle : counting memory allocation and deallocation, particularly in loops. This way, we can detect programs which compute within a constant amount of space. This method can easily be expressed as property on control flow graphs. Because analyses on data’s behaviour are syntactic, they can be done at compile time. Because they are only static, those analyses are not always computable or easily computable and approximations are needed. “Size-Change Principle” from C. S. Lee, N. D. Jones et A. M. Ben-Amram presented a method to predict termination by observing resources evolution and a lot of research came from this theory. Until now, these implicit complexity theories were essentially applied on more or less toy languages. This thesis applies implicit computational complexity methods into “real life” programs by manipulating intermediate representation languages in compilers. This give an accurate idea of the actual expressivity of these analyses and show that implicit computational complexity and compilers communities can fuel each other fruitfully. As we show in this thesis, the methods developed are quite generals and open the way to several new applications
La théorie de la complexité´e s’intéresse à la gestion des ressources, temps ou espace, consommés par un programmel ors de son exécution. L’analyse statique nous permet de rechercher certains critères syntaxiques afin de catégoriser des familles de programmes. L’une des approches les plus fructueuses dans le domaine consiste à observer le comportement potentiel des données manipulées. Par exemple, la détection de programmes “non size increasing” se base sur le principe très simple de compter le nombre d’allocations et de dé-allocations de mémoire, en particulier au cours de boucles et on arrive ainsi à détecter les programmes calculant en espace constant. Cette méthode s’exprime très bien comme propriété sur les graphes de flot de contrôle. Comme les méthodes de complexité implicite fonctionnent à l’aide de critères purement syntaxiques, ces analyses peuvent être faites au moment de la compilation. Parce qu’elles ne sont ici que statiques, ces analyses ne sont pas toujours calculables ou facilement calculables, des compromis doivent être faits en s’autorisant des approximations. Dans le sillon du “Size-Change Principle” de C. S. Lee, N. D. Jones et A. M. Ben-Amram, beaucoup de recherches reprennent cette méthode de prédiction de terminaison par observation de l’évolution des ressources. Pour le moment, ces méthodes venant des théories de la complexité implicite ont surtout été appliquées sur des langages plus ou moins jouets. Cette thèse tend à porter ces méthodes sur de “vrais” langages de programmation en s’appliquant au niveau des représentations intermédiaires dans des compilateurs largement utilises. Elle fournit à la communauté un outil permettant de traiter une grande quantité d’exemples et d’avoir une idée plus précise de l’expressivité réelle de ces analyses. De plus cette thèse crée un pont entre deux communautés, celle de la complexité implicite et celle de la compilation, montrant ainsi que chacune peut apporter à l’autre
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Pankratov, Denis. "Communication complexity and information complexity." Thesis, The University of Chicago, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3711791.

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Information complexity enables the use of information-theoretic tools in communication complexity theory. Prior to the results presented in this thesis, information complexity was mainly used for proving lower bounds and direct-sum theorems in the setting of communication complexity. We present three results that demonstrate new connections between information complexity and communication complexity.

In the first contribution we thoroughly study the information complexity of the smallest nontrivial two-party function: the AND function. While computing the communication complexity of AND is trivial, computing its exact information complexity presents a major technical challenge. In overcoming this challenge, we reveal that information complexity gives rise to rich geometrical structures. Our analysis of information complexity relies on new analytic techniques and new characterizations of communication protocols. We also uncover a connection of information complexity to the theory of elliptic partial differential equations. Once we compute the exact information complexity of AND, we can compute exact communication complexity of several related functions on n-bit inputs with some additional technical work. Previous combinatorial and algebraic techniques could only prove bounds of the form Θ( n). Interestingly, this level of precision is typical in the area of information theory, so our result demonstrates that this meta-property of precise bounds carries over to information complexity and in certain cases even to communication complexity. Our result does not only strengthen the lower bound on communication complexity of disjointness by making it more exact, but it also shows that information complexity provides the exact upper bound on communication complexity. In fact, this result is more general and applies to a whole class of communication problems.

In the second contribution, we use self-reduction methods to prove strong lower bounds on the information complexity of two of the most studied functions in the communication complexity literature: Gap Hamming Distance (GHD) and Inner Product mod 2 (IP). In our first result we affirm the conjecture that the information complexity of GHD is linear even under the uniform distribution. This strengthens the Ω(n) bound shown by Kerenidis et al. (2012) and answers an open problem by Chakrabarti et al. (2012). We also prove that the information complexity of IP is arbitrarily close to the trivial upper bound n as the permitted error tends to zero, again strengthening the Ω(n) lower bound proved by Braverman and Weinstein (2011). More importantly, our proofs demonstrate that self-reducibility makes the connection between information complexity and communication complexity lower bounds a two-way connection. Whereas numerous results in the past used information complexity techniques to derive new communication complexity lower bounds, we explore a generic way, in which communication complexity lower bounds imply information complexity lower bounds in a black-box manner.

In the third contribution we consider the roles that private and public randomness play in the definition of information complexity. In communication complexity, private randomness can be trivially simulated by public randomness. Moreover, the communication cost of simulating public randomness with private randomness is well understood due to Newman's theorem (1991). In information complexity, the roles of public and private randomness are reversed: public randomness can be trivially simulated by private randomness. However, the information cost of simulating private randomness with public randomness is not understood. We show that protocols that use only public randomness admit a rather strong compression. In particular, efficient simulation of private randomness by public randomness would imply a version of a direct sum theorem in the setting of communication complexity. This establishes a yet another connection between the two areas. (Abstract shortened by UMI.)

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Smith, Peter. "Adaptive leadership: fighting complexity with complexity." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42728.

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CHDS State/Local
Contemporary crises have become increasingly complex and the methods of leading through them have failed to keep pace. If it is assumed that leadership matters—that it has a legitimate effect on the outcome of a crisis, then leaders have a duty to respond to that adaptation with modifications of their own. Using literature sources, the research explores crisis complexity, crisis leadership, and alternative leadership strategies. Specifically, the research evaluates the applicability of complexity science to current crises. Having identified the manner in which crises have changed, it focuses on the gap between contemporary crises and the current methods of crisis leadership. The paper pursues adaptive methods of leading in complex crises and examines a number of alternative strategies for addressing the gap. The research suggests that a combination of recognizing the complexity of contemporary crises, applying resourceful solutions, and continually reflecting on opportunities to innovate, may be an effective way to lead through complex crises using complex leadership.
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Chen, Lijie S. M. Massachusetts Institute of Technology. "Fine-grained complexity meets communication complexity." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122754.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 215-229).
Fine-grained complexity aims to understand the exact exponent of the running time of fundamental problems in P. Basing on several important conjectures such as Strong Exponential Time Hypothesis (SETH), All-Pair Shortest Path Conjecture, and the 3-Sum Conjecture, tight conditional lower bounds are proved for numerous exact problems from all fields of computer science, showing that many text-book algorithms are in fact optimal. For many natural problems, a fast approximation algorithm would be as important as fast exact algorithms. So it would be interesting to show hardness for approximation algorithms as well. But we had few techniques to prove tight hardness for approximation problems in P--In particular, the celebrated PCP Theorem, which proves similar approximation hardness in the world of NP-completeness, is not fine-grained enough to yield interesting conditional lower bounds for approximation problems in P.
In 2017, a breakthrough work of Abboud, Rubinstein and Williams [12] established a framework called "Distributed PCP", and applied that to show conditional hardness (under SETH) for several fundamental approximation problems in P. The most interesting aspect of their work is a connection between fine-grained complexity and communication complexity, which shows Merlin-Arther communication protocols can be utilized to give fine-grained reductions between exact and approximation problems. In this thesis, we further explore the connection between fine-grained complexity and communication complexity. More specifically, we have two sets of results. In the first set of results, we consider communication protocols other than Merlin-Arther protocols in [12] and show that they can be used to construct other fine-grained reductions between problems. [sigma]₂ Protocols and An Equivalence Class for Orthogonal Vectors (OV).
First, we observe that efficient [sigma]₂[superscripts cc] protocols for a function imply fine-grained reductions from a certain related problem to OV. Together with other techniques including locality-sensitive hashing, we establish an equivalence class for OV with O(log n) dimensions, including Max-IP/Min-IP, approximate Max-IP/Min-IP, and approximate bichromatic closest/further pair. · NP · UPP Protocols and Hardness for Computational Geometry Problems in 2⁰([superscript log*n]) Dimensions. Second, we consider NP · UPP protocols which are the relaxation of Merlin-Arther protocols such that Alice and Bob only need to be convinced with probability > 1/2 instead of > 2/3.
We observe that NP · UPP protocols are closely connected to Z-Max-IP problem in very small dimensions, and show that Z-Max-IP, l₂₋-Furthest Pair and Bichromatic l₂-Closest Pair in 2⁰[superscript (log* n)] dimensions requires n²⁻⁰[superscript (1)] time under SETH, by constructing an efficient NP - UPP protocol for the Set-Disjointness problem. This improves on the previous hardness result for these problems in w(log² log n) dimensions by Williams [172]. · IP Protocols and Hardness for Approximation Problems Under Stronger Conjectures. Third, building on the connection between IP[superscript cc] protocols and a certain alternating product problem observed by Abboud and Rubinstein [11] and the classical IP = PSPACE theorem [123, 155]. We show that several finegrained problems are hard under conjectures much stronger than SETH (e.g., the satisfiability of n⁰[superscript (1)]-depth circuits requires 2(¹⁻⁰[superscript (1)n] time).
In the second set of results, we utilize communication protocols to construct new algorithms. · BQP[superscript cc] Protocols and Approximate Counting Algorithms. Our first connection is that a fast BQP[superscript cc] protocol for a function f implies a fast deterministic additive approximate counting algorithm for a related pair counting problem. Applying known BQP[superscript cc] protocols, we get fast deterministic additive approximate counting algorithms for Count-OV (#OV), Sparse Count-OV and Formula of SYM circuits. · AM[superscript cc]/PH[superscript cc] Protocols and Efficient SAT Algorithms. Our second connection is that a fast AM[superscript cc] (or PH[superscript cc]) protocol for a function f implies a faster-than-bruteforce algorithm for a related problem.
In particular, we show that if the Longest Common Subsequence (LCS) problem admits a fast (computationally efficient) PH[superscript cc] protocol (polylog(n) complexity), then polynomial-size Formula-SAT admits a 2[superscript n-n][superscript 1-[delta]] time algorithm for any constant [delta] > 0, which is conjectured to be unlikely by a recent work of Abboud and Bringmann [6].
by Lijie Chen.
S.M.
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Gopalakrishnan, K. S. "Complexity cores in average-case complexity theory." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1473222.

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Brochenin, Rémi. "Separation logic : expressiveness, complexity, temporal extension." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2013. http://tel.archives-ouvertes.fr/tel-00956587.

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This thesis studies logics which express properties on programs. These logics were originally intended for the formal verification of programs with pointers. Overall, no automated verification method will be proved tractable here- rather, we give a new insight on separation logic. The complexity and decidability of some essential fragments of this logic for Hoare triples were not known before this work. Also, its combination with some other verification methods was little studied. Firstly, in this work we isolate the operator of separation logic which makes it undecidable. We describe the expressive power of this logic, comparing it to second-order logics. Secondly, we try to extend decidable subsets of separation logic with a temporal logic, and with the ability to describe data. This allows us to give boundaries to the use of separation logic. In particular, we give boundaries to the creation of decidable logics using this logic combined with a temporal logic or with the ability to describe data.
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Otto, James R. (James Ritchie). "Complexity doctrines." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=29104.

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We characterize various complexity classes as the images in set$ sp2,$ set$ sp{V},$ and set$ sp3$ of categories initial in various complexity doctrines. (A doctrine consists of the models of a theory of theories.) We so characterize the linear time, P space, linear space, P time, and Kalmar elementary functions as well as the linear time hierarchy relations. (Our machine model is multi-tape Turing machines with constant number of tapes.) These doctrines extend, using comprehensions, the first order doctrines GM and JB. We show, using dependent product diagrams, how to so extend the higher order doctrine LCC. However, using Church numerals, we show that the resulting LCC comprehensions do not provide enough control over higher order types to characterize complexity classes. We also show how to use sketches and orthogonality for almost equational specification.
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Ada, Anil. "Communication complexity." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121119.

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Communication complexity studies how many bits a certain number of parties need to communicate with each other in order to compute a function whose input is distributed among those parties. Although it is a natural area of investigation based on practical considerations, the main motivation comes from the myriad of applications in theoretical computer science.This thesis has three main parts, studying three different aspects of communication complexity.1. The first part is concerned with the k-party communication complexity of functions F:({0,1}^n)^k -> {0,1} in the 'number on the forehead' (NOF) model. This is a fundamental model with many applications. In this model we study composed functions f of g. These functions include most of the well-known and studied functions in communication complexity literature. A major goal is to understand which combinations of f and g lead to hard communication functions. In particular, due to important circuit applications, it is of great interest to understand how powerful the NOF model becomes when k is log n or more. Motivated by these goals, we show that there is an efficient O(log^3 n) cost simultaneous protocol for sym of g when k > 1+log n, sym is any symmetric function and g is any function. This class of functions includes some functions that were previously conjectured to be hard and our result rules this class out for possible very important circuit complexity applications. We also give Ramsey theoretic applications of our efficient protocol. In the setting of k < log n, we study more closely functions of the form majority of g, mod_m of g, and nor of g, where the latter two are generalizations of the well-known functions Inner Product and Disjointness respectively. We characterize the communication complexity of these functions with respect to the choice of g. As the main application, we answer a question posed by Babai et al. (SIAM Journal on Computing, 33:137--166, 2004) and determine the communication complexity of majority of qcsb, where qcsb is the "quadratic character of the sum of the bits" function. 2. The second part is about Fourier analysis of symmetric boolean functions and its applications in communication complexity and other areas. The spectral norm of a boolean function f:{0,1}^n -> {0,1} is the sum of the absolute values of its Fourier coefficients. This quantity provides useful upper and lower bounds on the complexity of a function in areas such as communication complexity, learning theory and circuit complexity. We give a combinatorial characterization for the spectral norm of symmetric functions. We show that the logarithm of the spectral norm is of the same order of magnitude as r(f)log(n/r(f)) where r(f) = max(r_0,r_1), and r_0 and r_1 are the smallest integers less than n/2 such that f(x) or f(x)parity(x) is constant for all x with x_1 + ... + x_n in [r_0, n-r_1]. We present some applications to the decision tree and communication complexity of symmetric functions. 3. The third part studies privacy in the context of communication complexity: how much information do the players reveal about their input when following a communication protocol? The unattainability of perfect privacy for many functions motivates the study of approximate privacy. Feigenbaum et al. (Proceedings of the 11th Conference on Electronic Commerce, 167--178, 2010) defined notions of worst-case as well as average-case approximate privacy, and presented several interesting upper bounds, and some open problems for further study. In this thesis, we obtain asymptotically tight bounds on the trade-offs between both the worst-case and average-case approximate privacy of protocols and their communication cost for Vickrey Auction, which is the canonical example of a truthful auction. We also prove exponential lower bounds on the approximate privacy of protocols computing the Intersection function, independent of its communication cost. This proves a conjecture of Feigenbaum et al.
La complexité de communication étudie combien de bits un groupe de joueurs donné doivent échanger entre eux pour calculer une function dont l'input est distribué parmi les joueurs. Bien que ce soit un domaine de recherche naturel basé sur des considérations pratiques, la motivation principale vient des nombreuses applications théoriques.Cette thèse comporte trois parties principales, étudiant trois aspects de la complexité de communication.1. La première partie discute le modèle 'number on the forehead' (NOF) dans la complexité de communication à plusieurs joueurs. Il s'agit d'un modèle fondamental en complexité de communication, avec des applications à la complexité des circuits, la complexité des preuves, les programmes de branchement et la théorie de Ramsey. Dans ce modèle, nous étudions les fonctions composeés f de g. Ces fonctions comprennent la plupart des fonctions bien connues qui sont étudiées dans la littérature de la complexité de communication. Un objectif majeur est de comprendre quelles combinaisons de f et g produisent des compositions qui sont difficiles du point de vue de la communication. En particulier, à cause de l'importance des applications aux circuits, il est intéressant de comprendre la puissance du modèle NOF quand le nombre de joueurs atteint ou dépasse log n. Motivé par ces objectifs nous montrons l'existence d'un protocole simultané efficace à k joueurs de coût O(log^3 n) pour sym de g lorsque k > 1 + log n, sym est une function symmétrique quelconque et g est une fonction arbitraire. Nous donnons aussi des applications de notre protocole efficace à la théorie de Ramsey.Dans le contexte où k < log n, nous étudions de plus près des fonctions de la forme majority de g, mod_m de g et nor de g, où les deux derniers cas sont des généralisations des fonctions bien connues et très étudiées Inner Product et Disjointness respectivement. Nous caractérisons la complexité de communication de ces fonctions par rapport au choix de g.2. La deuxième partie considère les applications de l'analyse de Fourier des fonctions symmétriques à la complexité de communication et autres domaines. La norme spectrale d'une function booléenne f:{0,1}^n -> {0,1} est la somme des valeurs absolues de ses coefficients de Fourier. Nous donnons une caractérisation combinatoire pour la norme spectrale des fonctions symmétriques. Nous montrons que le logarithme de la norme spectrale est du même ordre de grandeur que r(f)log(n/r(f)), avec r(f) = max(r_0,r_1) où r_0 et r_1 sont les entiers minimaux plus petits que n/2 pour lesquels f(x) ou f(x)parity(x) est constant pour tout x tel que x_1 + ... + x_n à [r_0,n-r_1]. Nous présentons quelques applications aux arbres de décision et à la complexité de communication des fonctions symmétriques.3. La troisième partie étudie la confidentialité dans le contexte de la complexité de communication: quelle quantité d'information est-ce que les joueurs révèlent sur leur input en suivant un protocole donné? L'inatteignabilité de la confidentialité parfaite pour plusieurs fonctions motivent l'étude de la confidentialité approximative. Feigenbaum et al. (Proceedings of the 11th Conference on Electronic Commerce, 167--178, 2010) ont défini des notions de confidentialité approximative dans le pire cas et dans le cas moyen, et ont présenté plusieurs bornes supérieures intéressantes ainsi que quelques questions ouvertes. Dans cette thèse, nous obtenons des bornes asymptotiques précises, pour le pire cas aussi bien que pour le cas moyen, sur l'échange entre la confidentialité approximative de protocoles et le coût de communication pour les enchères Vickrey Auction, qui constituent l'exemple canonique d'une enchère honnête. Nous démontrons aussi des bornes inférieures exponentielles sur la confidentialité approximative de protocoles calculant la function Intersection, indépendamment du coût de communication. Ceci résout une conjecture de Feigenbaum et al.
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Mariotti, Humberto, and Cristina Zauhy. "Managing Complexity." Universidad Peruana de Ciencias Aplicadas (UPC), 2014.

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Abstract:
This article is a brief introduction to complexity, complex thinking and complexitymanagement. Its purpose is to present an update on the applications of the complexitysciences particularly to the universe of corporations and management. It includes anexample taken from the globalized world and two more stories from the corporateenvironment. Some details on how to think about complexity and how to apply theconceptual and operative tools of complex thinking are provided. The article ends withsome remarks on personal, interpersonal and corporate benefits of the complexthinking.
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Books on the topic "Complexity"

1

Watanabe, Osamu, ed. Kolmogorov Complexity and Computational Complexity. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77735-6.

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1958-, Watanabe Osamu, ed. Kolmogorov complexity and computational complexity. Berlin: Springer-Verlag, 1992.

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Watanabe, Osamu. Kolmogorov Complexity and Computational Complexity. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992.

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Complexity and postmodernism: Understanding complex systems. London: Routledge, 1998.

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Givón, T., and Masayoshi Shibatani, eds. Syntactic Complexity. Amsterdam: John Benjamins Publishing Company, 2009. http://dx.doi.org/10.1075/tsl.85.

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Miestamo, Matti, Kaius Sinnemäki, and Fred Karlsson, eds. Language Complexity. Amsterdam: John Benjamins Publishing Company, 2008. http://dx.doi.org/10.1075/slcs.94.

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Dehmer, Matthias, Frank Emmert-Streib, and Herbert Jodlbauer, eds. Entrepreneurial Complexity. Boca Raton, FL : CRC Press, 2018.: CRC Press, 2019. http://dx.doi.org/10.1201/9781351250849.

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Skobelev, Petr, and George Rzevski. Managing Complexity. Warrendale, PA: SAE International, 2014. http://dx.doi.org/10.4271/1845649362.

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Hickey, Anthony J., and Hugh D. C. Smyth. Pharmaco-Complexity. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-7856-1.

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Glattfelder, James B. Decoding Complexity. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33424-5.

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Book chapters on the topic "Complexity"

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Jörg, Ton. "The Complexity of Complexity." In New Thinking in Complexity for the Social Sciences and Humanities, 197–206. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1303-1_13.

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Allender, Eric. "The Complexity of Complexity." In Computability and Complexity, 79–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50062-1_6.

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Lee, Li Way, and Aaron Keathley. "Complexity: The Complexity Fever." In 45 Conversations About Behavioral Economics, 35–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05046-6_9.

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Klir, George J. "Complexity." In Facets of Systems Science, 135–57. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1331-5_8.

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Cvitkovic, Emilio. "Complexity." In Competition, 193–225. London: Palgrave Macmillan UK, 1993. http://dx.doi.org/10.1007/978-1-349-12857-0_8.

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Boy, Guy André. "Complexity." In Human–Computer Interaction Series, 87–106. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30270-6_5.

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Forsdyke, Donald R. "Complexity." In Evolutionary Bioinformatics, 267–91. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7771-7_14.

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Peitgen, Heinz-Otto, Hartmut Jürgens, Dietmar Saupe, Evan Maletsky, Terry Perciante, and Lee Yunker. "Complexity." In Fractals for the Classroom: Strategic Activities Volume One, 69–108. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4613-9047-3_3.

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Hammer, Barbara. "Complexity." In Learning with recurrent neural networks, 103–31. London: Springer London, 2000. http://dx.doi.org/10.1007/bfb0110021.

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Steinhart, Eric. "Complexity." In Believing in Dawkins, 23–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43052-8_2.

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Conference papers on the topic "Complexity"

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Flack, Jessica. "Complexity begets complexity." In The 2021 Conference on Artificial Life. Cambridge, MA: MIT Press, 2021. http://dx.doi.org/10.1162/isal_a_00470.

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MORIN, EDGAR. "RESTRICTED COMPLEXITY, GENERAL COMPLEXITY." In Worldviews, Science and Us - Philosophy and Complexity. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812707420_0002.

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"Proceedings of Computational Complexity (Formerly Structure in Complexity Theory)." In Proceedings of Computational Complexity (Formerly Structure in Complexity Theory). IEEE, 1996. http://dx.doi.org/10.1109/ccc.1996.507662.

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Linial, Nati, and Adi Shraibman. "Learning Complexity vs. Communication Complexity." In 2008 23rd Annual IEEE Conference on Computational Complexity. IEEE, 2008. http://dx.doi.org/10.1109/ccc.2008.28.

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Agrawal, M., and V. Arvind. "A note on decision versus search for graph automorphism." In Proceedings of Computational Complexity (Formerly Structure in Complexity Theory). IEEE, 1996. http://dx.doi.org/10.1109/ccc.1996.507689.

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"Author index." In Proceedings of Computational Complexity (Formerly Structure in Complexity Theory). IEEE, 1996. http://dx.doi.org/10.1109/ccc.1996.507693.

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Cerra, Daniele, and Mihai Datcu. "Algorithmic Cross-Complexity and Relative Complexity." In 2009 Data Compression Conference (DCC). IEEE, 2009. http://dx.doi.org/10.1109/dcc.2009.6.

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Kushilevitz, Eyal, and Enav Weinreb. "On the complexity of communication complexity." In the 41st annual ACM symposium. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1536414.1536479.

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Babai, Laszlo, Peter Frankl, and Janos Simon. "Complexity classes in communication complexity theory." In 27th Annual Symposium on Foundations of Computer Science (sfcs 1986). IEEE, 1986. http://dx.doi.org/10.1109/sfcs.1986.15.

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Arenas, Marcelo, Martin Munoz, and Cristian Riveros. "Descriptive Complexity for counting complexity classes." In 2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS). IEEE, 2017. http://dx.doi.org/10.1109/lics.2017.8005150.

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Reports on the topic "Complexity"

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Ackermann, Mark R., Nancy Kay Hayden, and Wendell Jones. Complexity and Simplicity: Putting Complexity Science in Perspective. Office of Scientific and Technical Information (OSTI), October 2018. http://dx.doi.org/10.2172/1481586.

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White, D., M. Stowell, and K. Lange. Automatic Complexity Reduction. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1179112.

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Carvalho, Leandro, and Dan Silverman. Complexity and Sophistication. Cambridge, MA: National Bureau of Economic Research, July 2019. http://dx.doi.org/10.3386/w26036.

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Salant, Yuval, and Jorg Spenkuch. Complexity and Choice. Cambridge, MA: National Bureau of Economic Research, April 2022. http://dx.doi.org/10.3386/w30002.

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Enke, Benjamin, Thomas Graeber, and Ryan Oprea. Complexity and Time. Cambridge, MA: National Bureau of Economic Research, March 2023. http://dx.doi.org/10.3386/w31047.

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Blakesley, Paul J. Operational Shock Complexity Theory. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada437516.

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Janusz, Paul E. The Complexity Analysis Tool. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada201700.

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Valle Jr, Vicente. Chaos, Complexity and Deterrence. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada432927.

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Streufert, Siegfried, Rosanne M. Pogash, and Mary T. Piasecki. Training for Cognitive Complexity. Fort Belvoir, VA: Defense Technical Information Center, March 1987. http://dx.doi.org/10.21236/ada181828.

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Cordwell, William. Complexity of the GNFS. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1647525.

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